個人在Party中的社會行為
Netlogo是個讓我們可以模擬個人在社會群體行為的工具，打開Files|Models Library|Social Science|Party，然後就會出現如圖的畫面。
當載入完畢時，會出現如圖：
會發現一些有趣的現象，隨著party的進行，一群群男女個數很平均的群體，最後都變成了男、女各別獨佔的情形，也就是，最後都變成一堆男、或是一堆女所組成的情形，而且男、女獨佔的數量都是很大。
為什麼會產生這種現象？你可以試著來解釋這種行為嗎？
setup: 內有tolerance參數，來調整
go: 反覆按下go，可以開始/停止，分群的狀態
step-once: 一開始分為幾組
藉由調整tolerance的參數值，來提供解釋這種行為的原因?tolerance是指在群組中，同性可以容忍異性的範圍，如果值為.25，則表示當10個人的群體，其異性個數中超過3人，就會造成同性的"un-comfortable"，就表示同性中有人會離開原群組，而另往它組尋求發展了。
To make sure all groups of 10 have both sexes, at what level should we set the tolerance? Test your predictions on the model. Can you see any other factors or variables that might affect the male to female ratio within each group? Make predictions and test your ideas within this model. Feel free to manipulate more than one variable at a time.
As you are testing your hypotheses, you will notice that patterns are emerging from the data. For example, if you keep the number of people at the party constant but gradually increase the tolerance level, more mixed groups appear.
How high does the tolerance value have to be before you get mixed groups? What percent tolerance tends to produce what percentage of mixing?
